Jon D
. Duk
e
MD
, MS
OHDSI Annual S
ymposium
Oct
ober 20
th
,
2015
T
r
ansla
tion
of Open-Source
Analytics
in
t
o P
atien
t-Cen
t
er
ed
Care
Funding Disclosur
es
•
Funding fr
om Ba
yer
,
Janssen, Lilly
, Mer
ck
–
R
esearch
–
Consulting
–
Coming up with
gr
eat drug names (
Zaxyr
bear
d)
W
e’
v
e Arriv
ed!
© Univer
sal Studios. All rights R
eser
ved
© Univer
sal Studios. All rights R
eser
ved
© Univer
sal Studios. All rights R
eser
ved
© Univer
sal Studios. All rights R
eser
ved
© Univer
sal Studios. All rights R
eser
ved
The ‘Bedside’
of
Drug Sa
f
e
ty In
f
orma
tics
Communic
a
tion of
new and
es
t
ablished drug sa
f
ety
evidence t
o
impr
ov
e patien
t c
ar
e
Adv
erse
R
eactions
•
Nausea
•
V
omiting
•
Headache
•
Dizziness
•
Rash
•
Pruritis
•
Diarrhea
•
Urtic
aria
•
F
ev
er
P
ost-Mark
eting E
vents
•
Angioedema
•
Stev
ens-Johnson
•
Hypersensitivity
•
Thr
ombocy
topenia
•
Anaph
ylactic r
eaction
•
TEN
•
Ery
thema multif
orme
•
Hepatitis
•
Urticaria
(76%)
(69%)
(66%)
(63%)
(60%)
(59%)
(57%)
(51%)
(46%)
(29%)
(24%)
(47%)
(42%)
(28%)
(21%)
(22%)
(26%)
(51%)
Common
Things Being Common
70
103
111
118
121
127
165
185
227
241
384
0
50
100
150
200
250
300
350
400
All Drugs
Bispho
sphonates
Beta Blocke
rs
Benzodiaz
epines
NSAIDs
Statins
ACE-Inhibi
tors
Proton P
ump Inhibit
ors
5-HT1 Ag
onists (Tript
ans)
Atypical
Antipsycho
tics
SSRI's
Mean Number of ADE's per label
Drug Class
ADEs per Label f
or 10 Common Drug Classes
70
103
111
118
121
127
165
185
227
241
384
0
50
100
150
200
250
300
350
400
All Drugs
Bispho
sphonates
Beta Blocke
rs
Benzodiaz
epines
NSAIDs
Statins
ACE-Inhibi
tors
Proton P
ump Inhibit
ors
5-HT1 Ag
onists (Tript
ans)
Atypical
Antipsycho
tics
SSRI's
Mean Number of ADE's per label
Drug Class
ADEs per Label f
or 10 Common Drug Classes
0
100
200
300
400
500
600
1930
1940
1950
1960
1970
1980
1990
2000
2010
2020
Labeled Adver
se R
eaction
s by
Y
ear of Approv
al
Labeled ADE's
En
t
er PENEL
OPE
P
er
sonaliz
ed
E
xplor
at
ory
N
a
vig
ation
&
E
v
aluation
O
f
L
abels f
or
P
r
oduct
E
ff
ec
ts
PENEL
OPE
•
PENEL
OPE lev
er
ages
OHDSI’
s evidence
gener
ation and cur
ation t
ools to pr
ovide
con
t
e
xt t
o
sa
f
ety inf
orma
tion on drug
labels
•
The natur
e of this
cont
e
xt ma
y dif
f
er
f
or
dif
f
eren
t st
ak
eholder
s (e.
g., pr
ovider
s,
r
esear
cher
s, pa
tien
ts)
A Big Supporting Cas
t
ACHI
LLES
:
Dat
abase
pr
ofiling
CIRCE
:
Cohort
definition
HERACLE
S
:
Cohort
char
acterization
HERMES
:
V
ocabulary
e
xplor
ation
LAERTES
:
Drug-AE
evidence base
HOMER
:
P
opulation-level
causality
assessment
PLA
T
O
:
P
atient-lev
el
pr
edictive
modeling
LAER
TE
S
Drugs
(RxNorm)
Conditions
(SNOMED)
Spontaneous
adverse
event data
(FAERS, VigiBa
se
â„¢,
ClinicalTrials.go
v)
MedDRA
-> SNOMED
Freetext,
ATC
-
>
RxNorm
Literature
(PubMed,
SemMed)
MeSH, UMLS
-> SNOMED
MeSH,
UMLS
-
>
RxNorm
Product
labeling
(SPL, SPC)
Freetext -
>
MedDRA®
-> SNOMED
SPL Set
ID
-
>
RxNorm
Indications
/
Contraindicatio
ns
(FDBâ„¢)
ICD-9-
CM
-> SNOMED
NDC/GenSeq
Num
-
>
RxNorm
Observational
healthcare
data
(claims
+ EHR)
ICD-9-CM,
ICD-
10
-> SNOMED
NDC/GPI/ATC
-
>
RxNorm
Drug
classification
s
(ATC, NDF-RT)
Condition
classification
s
(MedDRA®,
Ontology
of
Adverse Events)
Source to
Drug
Mapping
Source
to HOI
Mapping
E
vidence
Sources
Shall W
e T
ak
e a Look?
PENEL
OPE - it t
ak
es a c
ommunity!
Anthon
y Sena
Janssen
Eric
a V
oss
Janssen
Mat
t Levine
Columbia
Fr
ank
DeF
alco
Janssen
Hamed Abe
dtash
Indiana U
Lee Ev
an
s
L
TC Consulting
Rich Boyc
e
UPit
t
W
en Zhang
UPit
t
P
atrick R
yan
Janssen
Join the journey
In
t
eres
ted in OHDSI?
Ques
tions or commen
ts?
32